Journal
JOURNAL OF EXPERIMENTAL BOTANY
Volume 61, Issue 8, Pages 2171-2183Publisher
OXFORD UNIV PRESS
DOI: 10.1093/jxb/erp375
Keywords
Crop modelling; genotypexenvironment interaction; photosynthesis; quantitative analysis; QTL mapping; systems approach
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There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models often contain many empirical elements, and model parameters may have little biological meaning. Building on the experience in designing the relatively new model GECROS, we believe models can be made less empirical by employing existing physiological understanding and mathematical tools. In view of the potential added value of robust crop modelling to classical quantitative genetics, model input parameters are increasingly considered to represent 'genetic coefficients'. The advent of functional genomics and systems biology enables the elucidation of the molecular genetic basis of these coefficients. A number of case studies, in which the effects of quantitative trait loci or genes have been incorporated into existing ecophysiological models, have shown the promise of using models in analysing genotype-phenotype relationships of some crop traits. For further progress, crop models must be upgraded based on understanding at lower organizational levels for complicated phenomena such as sink formation in response to environmental cues, sink feedback on source activity, and photosynthetic acclimation to the prevailing environment. Within this context, the recently proposed 'crop systems biology', which combines modern genomics, traditional physiology and biochemistry, and advanced modelling, is believed ultimately to realize the expected roles of in silico modelling in narrowing genotype-phenotype gaps. This review summarizes recent findings and our opinions on perspectives for modelling genotypexenvironment interactions at crop level.
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